Gas hydrates are found in significant quantities on the North Slope of Alaska in subpermafrost sand units and intermixed in lower portions of permafrost within the hydrate stability window. While conventional surface seismic data and established imaging methods can indicate the presence of gas hydrate reservoirs, producing high-resolution images of (seismically) thin layers remains challenging due to the preferential attenuation of the higher-frequency data components. An alternative strategy is to use distributed acoustic sensing (DAS) involving cementing optical fibers into boreholes to measure seismic wavefield energy closer to the strata of interest using vertical seismic profiling (VSP). DAS VSP imaging takes advantage of the shorter travel paths and reduced attenuation to generate higher-resolution near-well images. We illustrate these benefits on a DAS VSP data set acquired at the Hydrate-01 stratigraphic test well located in the Prudhoe Bay Unit of Alaska where significant gas hydrate deposits have been detected in two subpermafrost sand layers that are intended for long-duration production testing. Our DAS data preprocessing workflow effectively isolates the upgoing compressional-wave (P-wave) reflections required for subsurface acoustic imaging. After applying three-dimensional (3-D) tomography to improve the quality of the 3-D migration velocity model, we use 3-D reverse-time migration (RTM) to develop high-quality images of the two target sands and minor near-well faulting. We validate our RTM images through highly accurate well-ties with previously acquired petrophysical log data. This study demonstrates that combining 3-D RTM imaging with DAS VSP data provides significant value to gas hydrate and similar projects, and it suggests that more advanced inversion approaches such as (elastic) least-squares RTM could recover higher-resolution and more quantitative estimates of subsurface reflectivity, which would be valuable for refining the understanding of gas hydrate systems.
We present an overview of reproducible 3D seismic data processing and imaging using the Madagascar open-source software package. So far, there has been a limited number of studies on the processing of real 3D data sets using open-source software packages. Madagascar with its wide range of individual programs and tools available provides the capability to fully process 3D seismic data sets. The goal is to provide a streamlined illustration of the approach for the implementation of 3D seismic data processing and imaging using the Madagascar open-source software package. A brief introduction is first given to the Madagascar open-source software package and the publicly available 3D Teapot Dome seismic data set. Several processing steps are applied to the data set, including amplitude gaining, ground roll attenuation, muting, deconvolution, static corrections, spike-like random noise elimination, normal moveout (NMO) velocity analysis, NMO correction, stacking, and band-pass filtering. A 3D velocity model in depth is created using Dix conversion and time-to-depth scaling. Three-dimensional poststack depth migration is then performed followed by [Formula: see text]-[Formula: see text] deconvolution and structure-enhancing filtering of the migrated image to suppress random noise and enhance the useful signal. We show that Madagascar, as a powerful open-source environment, can be used to construct a basic workflow to process and image 3D seismic data in a reproducible manner.
Summary Elastic time-reverse imaging offers a robust wavefield-based approach for locating microseismic events; however, event location accuracy greatly depends on the veracity of the elastic velocity models (i.e., VP and VS) used for wave propagation. In this study, we propose a methodology for microseismic image-domain wavefield tomography using the elastic wave equation and zero-lag and extended source images, the focusing of which is used as a quality control metric for velocity models. The objective function is designed to measure the focusing of time-reversed microseismic energy in zero-lag and extended event images. The function applies penalty operators to source images to highlight poorly focused residual energy caused by backpropagation through erroneous velocity models. Minimizing the objective function leads to a model optimization problem aimed at improving the image-focusing quality. P- and S-wave velocity model updates are computed using the adjoint-state method and build on the zero-lag and extended image residuals that satisfy the differential semblance optimization criterion. Synthetic experiments demonstrate that one can construct accurate elastic velocity models using the proposed method, which can significantly improve the focusing of imaged events leading to, e.g., enhanced fluid-injection programs.
Accurately estimating event locations is of significant importance in microseismic investigations because this information greatly contributes to the overall success of hydraulic fracturing monitoring programs. Full-wavefield time-reverse imaging (TRI) using one or more wave-equation imaging conditions offers an effective methodology for locating surface-recorded microseismic events. To be most beneficial in microseismic monitoring programs, though, the TRI procedure requires using accurate subsurface models that account for elastic media effects. We develop a novel microseismic (extended) PS energy imaging condition that explicitly incorporates the stiffness tensor and exhibits heightened sensitivity to isotropic elastic model perturbations compared to existing imaging conditions. Numerical experiments demonstrate the sensitivity of microseismic TRI results to perturbations in P- and S-wave velocity models. Zero-lag and extended microseismic source images computed at selected subsurface locations yields useful information about 3D P- and S-wave velocity model accuracy. Thus, we assert that these image volumes potentially can serve as the input into microseismic elastic velocity model building algorithms.
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